Miatz playground

The Map vs the Clickstream

Your assumed journey against what the data actually shows.

Coming to the Build-LabBrowser (JS)Designdes
The Demystify signature

the assumed curve and the real data curve share one set of axes in different colors — the gap between where a team thinks friction lives and where people actually drop off becomes one visual instead of two decks nobody compares

How it works

What goes in, what comes out

What it does

Learner builds a journey map — touchpoints plus an emotion curve — from a team's stated assumptions about a flow, predicting the biggest drop-off point first. The engine then overlays real, synthetic, anonymized clickstream and drop-off data on the exact same timeline.

You bring

place touchpoints on the timeline; draw the predicted emotion curve; predict the biggest drop-off point before reveal

You get

an overlaid dual chart of the assumed emotion curve against the actual drop-off curve, with the gap distance scored at each touchpoint

You control

flow picker (3 seeded flows: onboarding, checkout, support); emotion-curve granularity (5-point / 10-point); overlay reveal timing

Where it's used

Module 'Research at Machine Speed' L2 demo + case-study landing page as a BOFU trust-builder

customer journey mappingemotion curveassumption vs datadrop-off analysis

Concepts click when you open the machinery.

Three labs are already live and free — the same hands-on style this playground brings to its module.